The Impact of Open Data – Initial Findings from Case Studies

The GovLab is excited to participate this week in ConDatos, the largest open data event in South America, and one of the largest in the world. Given our interest in the reinvention of governance for the 21st century, open data is quite naturally at the core of our research.

At ConDatos, GovLab’s co-founder and chief of research Stefaan Verhulst will share insights gained from our current collaboration with Omidyar Network on a series of open data case studies. These case studies – 19, in total – are designed to provide a detailed examination of the various ways open data is being used around the world, across geographies and sectors, and to draw some over-arching lessons. The case studies are built from extensive research, including in-depth interviews with key participants in the various open data projects under study.

We are about halfway through our research now, having drafted ten of the case studies (see below for list), and this seems a good moment to consider some of the insights we’ve already gained. The complete selection of case studies, along with an overarching report on the key findings they surfaced, will be released later this fall.

Ways in which open data impacts lives

Broadly, we have identified four main ways in which open data is transforming economic, social, cultural and political life, and hence improving people’s lives.

First, open data is improving government, primarily by helping tackle corruption, improving transparency, and enhancing public services and resource allocation.

Open data is also empowering citizens to take control of their lives and demand change; this dimension of impact is mediated by more informed decision making and new forms of social mobilization, both facilitated by new ways of communicating and accessing information.

Open data is also creating new opportunities for citizens and groups, by stimulating innovation and promoting economic growth and development.

Finally, open data is playing an increasingly important role in solving big public problems, primarily by allowing citizens and policymakers to engage in new forms of data-driven assessment and data-driven engagement.

Enabling Conditions

While these are the four main ways in which open data is driving change, we have seen wide variability in the amount and nature of impact across our case studies. Put simply, some projects are more successful than others; or some projects might be more successful in a particular dimension of impact, and less successful in others.

As part of our research, we have therefore tried to identify some enabling conditions that maximize the positive impact of open data projects. These four stand out:

Open data projects are most successful when they are built not from the efforts of single organizations or government agencies, but when they emerge from partnerships across sectors (and even borders). The role of intermediaries (e.g., the media and civil society groups) and “data collaboratives” are particularly important.

Several of the projects we have seen have emerged on the back of what we might think of as an open data public infrastructure – i.e., the technical backend and organizational processes necessary to enable the regular release of potentially impactful data to the public.

Clear open data policies, includingwell-defined performance metrics, are also essential; policymakers and political leaders have an important role in creating an enabling (yet flexible) legal environment that includes mechanisms for project assessments and accountability, as well as providing the type of high-level political buy-in that can empower practitioners to work with open data.

We have also seen that the most successful open data projects tend to be those that target a well-defined problem or issue. In other words, projects with maximum impact often meet a genuine citizen need.

Challenges

Impact is also determined by the obstacles and challenges that a project confronts. Some regions and some projects face a greater number of hurdles. These also vary, but we have found four challenges that appear most often in our case studies:

Projects in countries or regions with low capacity or “readiness” (indicated, for instance by low Internet penetration rates or hostile political environments) typically fare less well.

Projects that are unresponsive to feedbackand user needs are less likely to succeed than those that are flexible and able to adapt to what their users want.

Open data often exists in tension with risks such as privacy and security; often, the impact of a project is limited or harmed when it fails to take into account and mitigate these risks.

Although open data projects are often “hackable” and cheap to get off the ground, the most successful do require investments – of time and money – after their launch; inadequate resource allocation is one of the most common reasons for a project to fail.

These lists of impacts, enabling factors and challenges are, of course, preliminary. We continue to refine our research and will include a final set of findings along with our final report. In the meantime, we invite you to send in your feedback or thoughts on any of these issues. We especially welcome feedback that is accompanied by concrete examples and specific instances from open data projects around the world.